COVID-19 in Iran: What was done and what should be done?
Bibliographic record
Abstract
The current COVID-19 pandemic started in Wuhan, China, in December 2019. The World health Organization (WHO) declared the COVID-19 as a public health emergency of international concern on January 30, 2020, and recognized the situation as a pandemic on March 11, 2020. Around 135 million confirmed cases and around 2.9 million deaths until the first week of April 2021 have been among its direct impacts on human health. All countries have been affected in different degrees, and each of them has used different strategies to protect themselves against health and nonhealth consequences of this epidemic. Although all approaches are full of mistakes with fatal and painful results, some of them were successful in limiting the epidemic. One of the astonishing improvements is development of several vaccines in a relatively short period of time, which has increased hopes for epidemic control. This review aims to critically appraise the strategies for COVID-19 epidemic control in Iran since the beginning of the disease until the fourth peak of disease in March 2021.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".